Learning Track
AI Agents
Build intelligent systems that think and act.
A parent track covering every tier of AI agent development, from drag-and-drop no-code tools to full Python frameworks. Complete all three sub-tracks to earn the AI Agents certification.
Sub-Tracks
Build powerful AI agents without writing a single line of code.
Use visual, drag-and-drop platforms (n8n, Zapier, Make.com, Voiceflow) to wire together LLM calls, tools, and logic into fully functional AI agents. Includes n8n error handling + retry patterns, the honest 'when not to use no-code' lesson, and job readiness for AI automation roles.
First lesson: What Are AI Agents? Concepts and the Agent Loop
Compose agents visually with the power of LangChain underneath.
Use low-code platforms (LangFlow, Flowise, Dify, Relevance AI) to build agents with visual UIs. Includes self-hosting Flowise via Docker to a public VPS, a deep RAG pipeline design lesson (chunking + embeddings + vector stores + precision@5 evals), and job readiness.
First lesson: Low-Code Platforms Overview: LangFlow, Flowise, Dify, Relevance AI
Build agents from scratch in Python with full control.
Use Python frameworks (LangChain v0.2+ / LangGraph / LlamaIndex / CrewAI) and raw SDKs (Anthropic, OpenAI) to build production-grade AI agents. Includes the Model Context Protocol, multi-agent orchestration patterns, a formal passion project with three brief options, and job readiness for AI / agent engineer roles.
First lesson: Code-First Agent Fundamentals: Python, ReAct, and Tool Calling